1. Field of the Invention
The present invention relates to a point cloud data processing device, and specifically relates to a point cloud data processing device which extracts features of an object from point cloud data thereof and which automatically generates a three-dimensional model in a short time.
2. Description of the Related Art
As a method for generating a three-dimensional model from point cloud data of an object, a method of connecting adjacent points and forming polygons may be used. In this case, in order to form polygons from several tens of thousands to tens of millions of points of the point cloud data, enormous amounts of processing time are required, and this method is not useful. In view of this, the following techniques are disclosed in, for example, Japanese Unexamined Patent Application Publication (Translation of PCT Application) No. 2000-509150 and Japanese Unexamined Patent Applications Laid-open Nos. 2004-272459 and 2005-024370. In these techniques, only three-dimensional features (edges and planes) are extracted from point cloud data, and three-dimensional polylines are automatically generated.
In the invention disclosed in Japanese Unexamined Patent Application Publication (Translation of PCT Application) No. 2000-509150, a scanning laser device scans a three-dimensional object and generates point clouds. The point cloud is separated into a group of edge points and a group of non-edge points, based on changes in depths and normal lines of the scanned points. Each group is fitted to geometric original drawings, and the fitted geometric original drawings are extended and are crossed, whereby a three-dimensional model is generated.
In the invention disclosed in Japanese Unexamined Patent Application Laid-open No. 2004-272459, segments (triangular polygons) are formed from point cloud data, and edges and planes are extracted based on continuity, direction of normal line, or distance, of adjacent polygons. Then, the point cloud data of each segment is converted into a plane equation or a curve equation by the least-squares method and is grouped by planarity and curvature, whereby a three-dimensional model is generated.
In the invention disclosed in Japanese Unexamined Patent Application Laid-open No. 2005-024370, two-dimensional rectangular areas are set for three-dimensional point cloud data, and synthesized normal vectors of measured points in the rectangular areas are obtained. All of the measured points in the rectangular area are rotationally shifted so that the synthesized normal vector corresponds to a z-axis direction. Standard deviation σ of z value of each of the measured points in the rectangular area is calculated. Then, when the standard deviation σ exceeds a predetermined value, the measured point corresponding to the center point in the rectangular area is processed as noise.